The impact of communication technologies on life and relationship satisfaction

Previous studies have shown a relationship between the use of communications technology and well-being, particularly mediated through its effect on personal relationships. However, there is some debate over whether this effect is positive or negative. The present study explored this issue further, examining whether the effect varies depending on the type of communications technology, and the nature of the personal relationship. An online survey was conducted with 3,421 participants in three countries (Australia, UK and US). It examined the use of ten communication methods, overall satisfaction with life and satisfaction with four different kinds of relationships (close and extended family, and close and distant friends). Results indicate that richer communication methods, which include non-verbal cues, were positively associated with both overall satisfaction with life and satisfaction with relationships. These methods included face-to-face communication, and phone and video calls. Conversely, more restricted methods, such as text messaging and instant messaging, were negatively associated with both variables. Social networking was negatively associated with overall satisfaction, but not with satisfaction with relationships. The strength of the association between a communications method and satisfaction with a relationship varied depending on the type of relationship, but whether it was positive or negative did not change.

Place categorization and semantic mapping on a mobile robot

In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot with-out environment-specific training. Motivated by their ongoing success in various visual recognition tasks, we build our system upon a state-of-the-art convolutional network. We overcome its closed-set limitations by complementing the network with a series of one-vs-all classifiers that can learn to recognize new semantic classes online. Prior domain knowledge is incorporated by embedding the classification system into a Bayesian filter framework that also ensures temporal coherence. We evaluate the classification accuracy of the system on a robot that maps a variety of places on our campus in real-time. We show how semantic information can boost robotic object detection performance and how the semantic map can be used to modulate the robot’s behaviour during navigation tasks. The system is made available to the community as a ROS module.

Two ex situ fungal technologies to treat contaminated soil

Wood-degrading fungi are able to degrade a large range of recalcitrant pollutants which resemble the lignin biopolymer. This ability is attributed to the production of lignin-modifying enzymes, which are extracellular and non-specific. Despite the potential of fungi in bioremediation, there is still an understanding gap in terms of the technology. In this thesis, the feasibility of two ex situ fungal bioremediation methods to treat contaminated soil was evaluated. Treatment of polycyclic aromatic hydrocarbons (PAHs)-contaminated marsh soil was studied in a stirred slurry-phase reactor. Due to the salt content in marsh soil, fungi were screened for their halotolerance, and the white-rot fungi Lentinus tigrinus, Irpex lacteus and Bjerkandera adusta were selected for further studies. These fungi degraded 40 - 60% of a PAH mixture (phenanthrene, fluoranthene, pyrene and chrysene) in a slurry-phase reactor (100 ml) during 30 days of incubation. Thereafter, B. adusta was selected to scale-up and optimize the process in a 5 L reactor. Maximum degradation of dibenzothiophene (93%), fluoranthene (82%), pyrene (81%) and chrysene (83%) was achieved with the free mycelium inoculum of the highest initial biomass (2.2 g/l). In autoclaved soil, MnP was the most important enzyme involved in PAH degradation. In non-sterile soil, endogenous soil microbes together with B. adusta also degraded the PAHs extensively, suggesting a synergic action between soil microbes and the fungus. A fungal solid-phase cultivation method to pretreat contaminated sawmill soil with high organic matter content was developed to enhance the effectiveness of the subsequent soil combustion. In a preliminary screening of 146 fungal strains, 28 out of 52 fungi, which extensively colonized non-sterile contaminated soil, were litter-decomposing fungi. The 18 strains further selected were characterized by their production of lignin-modifying and hydrolytic enzymes, of which MnP and endo-1,4-β-glucanase were the main enzymes during cultivation on Scots pine (Pinus sylvestris) bark. Of the six fungi selected for further tests, Gymnopilus luteofolius, Phanerochaete velutina, and Stropharia rugosoannulata were the most active soil organic matter degraders. The results showed that a six-month pretreatment of sawmill soil would result in a 3.5 - 9.5% loss of organic matter, depending on the fungus applied. The pretreatment process was scaled-up for a 0.56 m3 reactor, in which perforated plastic tubes filled with S. rugosoannulata growing on pine bark were introduced into the soil. The fungal pretreatment resulted in a soil mass loss of 30.5 kg, which represents 10% of the original soil mass (308 kg). Despite the fact that Scots pine bark contains several antimicrobial compounds, it was a suitable substrate for fungal growth and promoter of the production of oxidative enzymes, as well as an excellent and cheap natural carrier of fungal mycelium. This thesis successfully developed two novel fungal ex situ bioremediation technologies and introduce new insights for their further full-scale application. Ex situ slurry-phase fungal reactors might be applied in cases when the soil has a high water content or when the contaminant bioavailability is low; for example, in wastewater treatment plants to remove pharmaceutical residues. Fungal solid-phase bioremediation is a promising remediation technology to ex situ or in situ treat contaminated soil.

Explorations in the distributional and semantic similarity of words

A straightforward computation of the list of the words (the `tail words' of the list) that are distributionally most similar to a given word (the `head word' of the list) leads to the question: How semantically similar to the head word are the tail words; that is: how similar are their meanings to its meaning? And can we do better? The experiment was done on nearly 18,000 most frequent nouns in a Finnish newsgroup corpus. These nouns are considered to be distributionally similar to the extent that they occur in the same direct dependency relations with the same nouns, adjectives and verbs. The extent of the similarity of their computational representations is quantified with the information radius. The semantic classification of head-tail pairs is intuitive; some tail words seem to be semantically similar to the head word, some do not. Each such pair is also associated with a number of further distributional variables. Individually, their overlap for the semantic classes is large, but the trained classification-tree models have some success in using combinations to predict the semantic class. The training data consists of a random sample of 400 head-tail pairs with the tail word ranked among the 20 distributionally most similar to the head word, excluding names. The models are then tested on a random sample of another 100 such pairs. The best success rates range from 70% to 92% of the test pairs, where a success means that the model predicted my intuitive semantic class of the pair. This seems somewhat promising when distributional similarity is used to capture semantically similar words. This analysis also includes a general discussion of several different similarity formulas, arranged in three groups: those that apply to sets with graded membership, those that apply to the members of a vector space, and those that apply to probability mass functions.

Three-year-olds are sensitive to semantic prominence during online language comprehension

Recent evidence from adult pronoun comprehension suggests that semantic factors such as verb transitivity affect referent salience and thereby anap- hora resolution. We tested whether the same semantic factors influence pronoun comprehension in young children. In a visual world study, 3-year- olds heard stories that began with a sentence containing either a high or a low transitivity verb. Looking behaviour to pictures depicting the subject and object of this sentence was recorded as children listened to a subsequent sentence containing a pronoun. Children showed a stronger preference to look to the subject as opposed to the object antecedent in the low transitivity condition. In addition there were general preferences (1) to look to the subject in both conditions and (2) to look more at both potential antecedents in the high transitivity condition. This suggests that children, like adults, are affected by semantic factors, specifically semantic prominence, when interpreting anaphoric pronouns.

Commercialization of sustainable energy technologies

Commercialization efforts to diffuse sustainable energy technologies (SETs1) have so far remained as the biggest challenge in the field of renewable energy and energy efficiency. Limited success of diffusion through government driven pathways urges the need for market based approaches. This paper reviews the existing state of commercialization of SETs in the backdrop of the basic theory of technology diffusion. The different SETs in India are positioned in the technology diffusion map to reflect their slow state of commercialization. The dynamics of SET market is analysed to identify the issues, barriers and stakeholders in the process of SET commercialization. By upgrading the ‘potential adopters’ to ‘techno-entrepreneurs’, the study presents the mechanisms for adopting a private sector driven ‘business model’ approach for successful diffusion of SETs. This is expected to integrate the processes of market transformation and entrepreneurship development with innovative regulatory, marketing, financing, incentive and delivery mechanisms leading to SET commercialization.

Adoption processes for EDM, EDI and BIM technologies in the construction industry

Three strategically important uses of IT in the construction industry are the storage and management of project documents on webservers (EDM), the electronic handling of orders and invoices between companies (EDI) and the use of 3-D models including non-geometrical attributes for integrated design and construction (BIM). In a broad longitudinal survey study of IT use in the Swedish Construction Industry the extent of use of these techniques was measured in 1998, 2000 and 2007. The results showed that EDM and EDI are currently already well-established techniques whereas BIM, although it promises the biggest potential benefits to the industry, only seems to be at the beginning of adoption. In a follow-up to the quantitative studies, the factors affecting the decisions to implement EDM, EDI and BIM as well as the actual adoption processes, were studied using semi-structured interviews with practitioners. The theoretical basis for the interview studies was informed by theoretical frameworks from IT-adoption theory, where in particular the UTAUT model has provided the main basis for the analyses presented here. The results showed that the decisions to take the above technologies into use are made on three differ- ent levels: the individual level, the organizational level in the form of a company, and the organiza- tional level in the form of a project. The different patterns in adoption can to some part be explained by where the decisions are mainly taken. EDM is driven from the organisation/project level, EDI mainly from the organisation/company level, and BIM is driven by individuals pioneering the technique.

Structural aspects of semantic-directed clusters

Knowledge-based clusters are studied from the structural point of view. Generalized descriptions for such clusters are stated and illustrated. Peculiarities of certain knowledge-based cluster configurations are highlighted. The adequacy of the connectives logical and (“and”) logical or (“exclusive-or”) in describing such clusters is justified. The definition of “concept” is elaborated from the clustering point of view and used to establish the equivalence between, descriptions of clusters and concepts. The order-independence of semantic-directed clustering approach is established formally based on axiomatic considerations.

The Organisation of Policy Meets the Commercialisation of Sex - Global Linkages, Policies, Technologies

During recent years the commercialisation of sex has increased and intensified both locally and globally. This thesis explores the commercialisation of bodies, sex and sexualities, particularly the sex trade, and the impact of rapidly evolving information and communication technologies on this globalising trade. The main focus of this work is on the policies, discourses and policy developments in the area especially in the Finnish context. The study is based on multidisciplinary theoretical sources through which the framework of multiple linkages relevant to the commercialisation of sex is conceptualised. The sex trade functions through a web of intersecting linkages of a substantive, economic, organisational, temporal, spatial, cultural, technological, as well as of legislative and policy nature. This framework of linkages forms the basis for the analysis of the main empirical data, namely qualitative interviews with thirty key managers and professionals, who are responsible for the preparation and implementation of policies on commercial sex. In addition, the thesis addresses the policies and policy practices on the sex trade through the analysis of national and international policy instruments. In addition to analysing the processes of the commercialisation of sex and its effects, the study also discusses their further implications for organisational policy-making, research, and society more generally. The thesis thus seeks to contribute to practice, research and theory on gender, management and organisations.

Information and Decision Technologies

Production scheduling in a flexible manufacturing system (FMS) is a real-time combinatorial optimization problem that has been proved to be NP-complete. Solving this problem needs on-line monitoring of plan execution and requires real-time decision-making in selecting alternative routings, assigning required resources, and rescheduling when failures occur in the system. Expert systems provide a natural framework for solving this kind of NP-complete problems.In this paper an expert system with a novel parallel heuristic approach is implemented for automatic short-term dynamic scheduling of FMS. The principal features of the expert system presented in this paper include easy rescheduling, on-line plan execution, load balancing, an on-line garbage collection process, and the use of advanced knowledge representational schemes. Its effectiveness is demonstrated with two examples.

A Study on the Success Potential of Multiple Mobile Payment Technologies

Payment systems all over the world have grown into a complicated web of solutions. This is more challenging in the case of mobile based payment systems. Mobile based payment systems are many and consist of different technologies providing different services. The diffusion of these various technologies in a market is uncertain. Diffusion theorists, for example Rogers, and Davis suggest how innovation is accepted in markets. In the case of electronic payment systems, the tale of Mondex vs Octopus throws interesting insights on diffusion. Our paper attempts to understand the success potential of various mobile payment technologies. We illustrate what we describe as technology breadth in mobile payment systems using data from payment systems all over the world (n=62). Our data shows an unexpected superiority of SMS technology, over other technologies like NFC, WAP and others. We also used a Delphi based survey (n=5) with experts to address the possibility that SMS will gain superiority in market diffusion. The economic conditions of a country, particularly in developing countries, the services availed and characteristics of the user (for example number of un-banked users in large populated countries) may put SMS in the forefront. This may be true more for micro payments using the mobile.

Volume modelling for emerging manufacturing technologies

The next generation manufacturing technologies will draw on new developments in geometric modelling. Based on a comprehensive analysis of the desiderata of next generation geometric modellers, we present a critical review of the major modelling paradigms, namely, CSG, B-Rep, non-manifold, and voxel models. We present arguments to support the view that voxel-based modellers have attributes that make it the representation scheme of choice in meeting the emerging requirements of geometric modelling.